\begin{table}[!h]
\centering
\caption{Comparison of baseline classifiers with fine‐tuned LLMs (Swiss Tweets validation set)}
\centering
\fontsize{10}{12}\selectfont
\begin{tabular}[t]{lccccc}
\toprule
Model & Precision & Recall & F1 score & Accuracy & F1 (Weighted)\\
\midrule
\cellcolor{gray!10}{Kotarcic et al. (2022)} & \cellcolor{gray!10}{0.7227301} & \cellcolor{gray!10}{0.1022562} & \cellcolor{gray!10}{0.1791633} & \cellcolor{gray!10}{0.9147444} & \cellcolor{gray!10}{0.8844401}\\
Perspective API & 1.0000000 & 0.0030170 & 0.0060158 & 0.9089634 & 0.8658903\\
\cellcolor{gray!10}{LLaMA 3 8 b} & \cellcolor{gray!10}{0.4419315} & \cellcolor{gray!10}{0.3827097} & \cellcolor{gray!10}{0.4101941} & \cellcolor{gray!10}{0.8998584} & \cellcolor{gray!10}{0.8965961}\\
DeepSeek R1 Qwen 14 b & 0.4963247 & 0.3606003 & 0.4177141 & 0.9085237 & 0.9018970\\
\cellcolor{gray!10}{DeepSeek R1 Qwen 32 b (8-bit)} & \cellcolor{gray!10}{0.5866058} & \cellcolor{gray!10}{0.3461696} & \cellcolor{gray!10}{0.4353998} & \cellcolor{gray!10}{0.9183103} & \cellcolor{gray!10}{0.9086030}\\
\bottomrule
\end{tabular}
\end{table}
